Reach and Citation of DataONE
Paige Alfonzo is a Ph.D. candidate at the University of Denver studying Research Methods and Statistics. She received my M.S. in Library Information Science in 2010 from the University of North Texas. She is a researcher whose expertise in social media methods and analysis draws from a variety of fields including statistics, higher education, information science, media studies, communication studies, and literary criticism. Having been trained in a variety of areas related to technology, society, and culture, she currently considers herself an Internet studies scholar grounded within the humanities and social sciences.
As part of our transition to a sustainable future (https://www.dataone.org/future), DataONE seeks to develop a comprehensive understanding of the way in which the organization is discussed and referenced in the broader community. This information will support strategic communication and outreach planning and provide insights into future collaborations and partnerships to be pursued.
Scholarly communications are one method of assessing recognition and DataONE maintains a database of articles published by DataONE and also articles citing DataONE. However, many references are non formal citations and exist on web pages or in blogs and other communications. Additionally, even within the published literature, there is variation in how and where DataONE is cited resulting in some articles not be accurately indexed.
This project will undertake several activities. First, the current database of publications and citing articles will be reviewed and transferred to a public bibliographic manager such as zotero, enabling community contributions to the library moving forward. In doing so, a thorough search of the literature will be conducted to ensure the library is up-to-date. Second, building from a previous project in DataONE that explored ARL library citation of DataONE, this internship will investigate incidence of DataONE citations and links on pages across the web. These will be categorized by various factors such as type of page, type of mention, where the link directs to etc. Research of this type will augment current usage data to help us understand which products and services are value by the community and to explore variation across stakeholder types.